Deputy Director of Provincial Key Laboratory at Shenyang Aerospace University, China
Dong Liu is an Associate Professor at the College of Automation, Shenyang Aerospace University, China. He is a leading researcher in the field of control theory and engineering, especially recognized for his work on data-driven control, model-free adaptive control, and secure control systems. He plays active roles in various national technical committees related to automation, command and control, and artificial intelligence.
Publication Profile
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Educational Background 🎓
Professional Experience 💼
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Associate Professor,
College of Automation, Shenyang Aerospace University
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Deputy Director,
Liaoning Provincial Key Laboratory of Advanced Flight Control and Simulation Technology
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Recognized as a High-Level Talent by Shenyang Municipality
Committee Roles:
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Committee Member, Technical Committee on Data-Driven Control, Learning, and Optimization (Chinese Association of Automation)
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Committee Member, Technical Committee on Intelligent Control and Systems (Chinese Command and Control Association)
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Committee Member, Technical Committee on Intelligent Detection and Motion Control Technology (Chinese Association for Artificial Intelligence)
Research Interests 🔬
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Data-Driven Control
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Model-Free Adaptive Control (MFAC)
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Secure Control Systems
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Sliding Mode Control
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Cyber-Physical Systems
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Prescribed Performance Control
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Aerospace Control Applications
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Event-Triggered and Reinforcement Learning-based Control
Awards and Honors🏆✨
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Recognized as High-Level Talent by the Shenyang Municipality
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Appointed Deputy Director of a Provincial Key Laboratory
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Holds Multiple Technical Committee Memberships in prestigious national associations
Conclusion🌟
Dr. Dong Liu is an influential scholar in control engineering, especially in data-driven and model-free adaptive control systems with an emphasis on robustness, security, and real-time applications in aerospace and cyber-physical systems. His high-impact journal publications and leadership roles in national technical committees underline his strong academic and technical contributions. He is actively shaping the future of intelligent control in China and internationally.
Publications 📚
📘 Data-driven second-order iterative sliding mode control for cyber–physical systems under prescribed performance and DoS attacks
✍️ Yijie Yang, Dong Liu, Xin Wang, Zhujun Wang
🗞️ Journal of Process Control, June 2025
🔗 DOI: 10.1016/j.jprocont.2025.103422
📘 Prescribed performance based data-driven adaptive sliding mode control for discrete-time nonlinear systems
✍️ Dong Liu, Yi-Jie Yang, Li-Ying Hao
🗞️ Journal of the Franklin Institute, March 2024
🔗 DOI: 10.1016/j.jfranklin.2024.01.021
📘 Data-Driven Bipartite Consensus Tracking for Nonlinear Multiagent Systems With Prescribed Performance
✍️ Dong Liu, Zhi-Peng Zhou, Tie-Shan Li
🗞️ IEEE Trans. on Systems, Man, and Cybernetics: Systems, 2023
🔗 DOI: 10.1109/TSMC.2022.3230504
📘 Event‐triggered model‐free adaptive control for nonlinear systems with output saturation
✍️ Dong Liu, Ning Liu, Tieshan Li
🗞️ Int. Journal of Robust and Nonlinear Control, August 2023
🔗 DOI: 10.1002/rnc.6747
📘 Data-Driven Adaptive Sliding Mode Control of Nonlinear Discrete-Time Systems With Prescribed Performance
✍️ Dong Liu, Guang-Hong Yang
🗞️ IEEE Trans. on Systems, Man, and Cybernetics: Systems, December 2019
🔗 DOI: 10.1109/TSMC.2017.2779564
📘 Prescribed Performance Model-Free Adaptive Integral Sliding Mode Control for Discrete-Time Nonlinear Systems
✍️ Dong Liu, Guang-Hong Yang
🗞️ IEEE Trans. on Neural Networks and Learning Systems, July 2019
🔗 DOI: 10.1109/TNNLS.2018.2881205
📘 Model-Free Adaptive Control Design for Nonlinear Discrete-time Processes with Reinforcement Learning Techniques
✍️ Dong Liu
🗞️ International Journal of Systems Science, July 2018
🔗 [Link not provided]
📘 Performance-based data-driven model-free adaptive sliding mode control for a class of discrete-time nonlinear processes
✍️ Dong Liu
🗞️ Journal of Process Control, June 2018
🔗 [Link not provided]
📘 Data-Driven Adaptive Sliding Mode Control of Nonlinear Discrete-Time Systems With Prescribed Performance
✍️ Dong Liu
🗞️ IEEE Trans. on Systems, Man, and Cybernetics: Systems, November 2017
🔗 [Link not provided]
📘 Event-based model-free adaptive control for discrete-time non-linear processes
✍️ Dong Liu
🗞️ IET Control Theory & Applications, September 2017
🔗 [Link not provided]
📘 Neural network-based event-triggered MFAC for nonlinear discrete-time processes
✍️ Dong Liu
🗞️ Neurocomputing, July 2017
🔗 [Link not provided]